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» A probabilistic framework for image segmentation
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CVPR
2010
IEEE
1135views Computer Vision» more  CVPR 2010»
14 years 3 months ago
Towards Weakly Supervised Semantic Segmentation by Means of Multiple Instance and Multitask Learning.
We address the task of learning a semantic segmentation from weakly supervised data. Our aim is to devise a system that predicts an object label for each pixel by making use of on...
Alexander Vezhnevets, Joachim Buhmann
IPMI
2003
Springer
14 years 1 months ago
Neighbor-Constrained Segmentation with 3D Deformable Models
A novel method for the segmentation of multiple objects from 3D medical images using inter-object constraints is presented. Our method is motivated by the observation that neighbor...
Jing Yang, Lawrence H. Staib, James S. Duncan
AMR
2006
Springer
157views Multimedia» more  AMR 2006»
13 years 11 months ago
SAFIRE: Towards Standardized Semantic Rich Image Annotation
Most of the currently existing image retrieval systems make use of either low-level features or semantic (textual) annotations. A combined usage during annotation and retrieval is ...
Christian Hentschel, Andreas Nürnberger, Ingo...
ICIP
2006
IEEE
14 years 9 months ago
An adaptive mixture color model for robust visual tracking
Global color characterization is a very powerful tool to model in a simple yet discriminant way the visual appearance of complex objects. A fixed reference model of this type can ...
Antoine Lehuger, Patrick Léchat, Patrick P&...
MICCAI
2004
Springer
14 years 9 months ago
Learning Coupled Prior Shape and Appearance Models for Segmentation
We present a novel framework for learning a joint shape and appearance model from a large set of un-labelled training examples in arbitrary positions and orientations. The shape an...
Xiaolei Huang, Zhiguo Li, Dimitris N. Metaxas